配网中光伏逆变器最优潮流追踪的分布式算法
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摘要
在量测、定位、通信技术,以及逆变器输出可快速设定的电力电子化技术成熟背景下,针对配电网中分布式光伏逆变器最优潮流追踪问题,提出一种时变、线性化的优化模型。该模型依据优化周期极短、电网状态量在优化周期内数值变化微小的特点,基于泰勒展开,将优化时段内的目标函数、约束条件线性化,从而将非线性优化问题转化为序列线性优化问题。这一序列线性化方法较全程线性化假设在精度上有显著提高。进一步利用交替方向乘子算法,将上述线性规划问题推演为分布式计算格式,即各光伏逆变器仅需获取相邻节点有限的变量信息,即可完成对自身运行基点的优化,并得到全局一致性的优化结果。算例分析表明,所提算法可以实现光伏逆变器对最优潮流的实时追踪,从而使配电网更好地适应高比例光伏电源的接入,提高配电网主动性与运行效率。
This paper considered the real-time optimal power flow control of distributed photovoltaic inverters in distribution networks with well-developed measurement and communication technologies. A time-varying, linear optimization method was proposed for higher accuracy and computation speed, where Taylor expansion was used to linearize the objective function and constraints under the premise of small variable changes during the short control period, which makes the optimal problem linear. This time-varying linear approximation is more accurate than the constant linearization. By leveraging the so-called alternating direction method of multipliers, a distributed control method was then conducted to overcome the difficulties arising from the centralized calculation. Applying the distributed control method makes distributed photovoltaic inverter controllers capable of optimizing their own power setpoints with only a little information obtained from neighbor nodes. Case study demonstrates that distribution networks will be more efficient and economical by adopting the real-time control method proposed in this paper.
This paper considered the real-time optimal power flow control of distributed photovoltaic inverters in distribution networks with well-developed measurement and communication technologies. A time-varying, linear optimization method was proposed for higher accuracy and computation speed, where Taylor expansion was used to linearize the objective function and constraints under the premise of small variable changes during the short control period, which makes the optimal problem linear. This time-varying linear approximation is more accurate than the constant linearization. By leveraging the so-called alternating direction method of multipliers, a distributed control method was then conducted to overcome the difficulties arising from the centralized calculation. Applying the distributed control method makes distributed photovoltaic inverter controllers capable of optimizing their own power setpoints with only a little information obtained from neighbor nodes. Case study demonstrates that distribution networks will be more efficient and economical by adopting the real-time control method proposed in this paper.
引文
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[2]黄欣科,王环,王一波,等.光伏发电系统并网点电压升高调整原理及策略[J].电力系统自动化,2014,38(3):112-117.Huang Xinke,Wang Huan,Wang Yibo,et al.Principleand strategies of voltage rise regulation for grid-connectedphotovoltaicgenerationsystematpointofcommoncoupling[J].AutomationofElectricPowerSystems,2014,38(3):112-117(in Chinese).
[3]Jahangiri P,Aliprantis D C.Distributed Volt/VAr controlby PV inverters[J].IEEE Transactions on Power Systems,2013,28(3):3429-3439.
[4]王颖,文福拴,赵波,等.高密度分布式光伏接入下电压越限问题的分析与对策[J].中国电机工程学报,2016,36(5):1200-1206.Wang Ying,Wen Fushuan,Zhao Bo,et al.Analysis andcountermeasuresofvoltage violationproblemscausedbyhigh-densitydistributedphotovoltaics[J].Proceedingsofthe CSEE,2016,36(5):1200-1206(in Chinese).
[5]Smith J W,Sunderman W,Dugan R,et al.Smart invertervolt/varcontrolfunctionsforhighpenetrationofPVondistributionsystems[C]//Proceedingsof2011IEEE/PESPower Systems Conference and Exposition.Phoenix,AZ,USA:IEEE,2011:1-6.
[6]Turitsyn K,Sulc P,Backhaus S,et al.Options for controlofreactivepowerbydistributedphotovoltaicgenerators[J].Proceedings of the IEEE,2011,99(6):1063-1073.
[7]Tonkoski R,Lopes L A C,El-Fouly T H M.CoordinatedactivepowercurtailmentofgridconnectedPVinvertersforovervoltagePrevention[J]. IEEETransactionsonSustainable Energy,2011,2(2):139-147.
[8]Bletterie B,Kadam S,Bolgaryn R,et al.Voltage controlwithPVinvertersinlowvoltagenetworks—Indepthanalysisofdifferentconceptsandparameterizationcriteria[J].IEEE Transactions on Power Systems,2017,32(1):177-185.
[9]Su Xiangjing,Masoum M A S,Wolfs P J.Optimal PVinverter reactive power control and real power curtailmenttoimproveperformanceofunbalancedfour-wireLVdistributionnetworks[J]. IEEETransactionsonSustainable Energy,2014,5(3):967-977.
[10] Guggilam S S,Dall’Anese E,Chen Y C,et al.ScalableoptimizationmethodsfordistributionnetworkswithhighPVintegration[J].IEEETransactionsonSmartGrid,2016,7(4):2061-2070.
[11]ZhangYijian, HongMingyi, Dall'AneseE, etal.Distributed controllers seeking AC optimal power flowsolutionsusingADMM[J].IEEETransactionsonSmartGrid,2018,9(5):4525-4537.
[12] Dall’AneseE, SimonettoA. Optimalpowerflowpursuit[J].IEEE Transactions on Smart Grid,2018,9(2):942-952.
[13]?ulcP,BackhausS,ChertkovM.Optimaldistributedcontrolofreactivepowerviathealternatingdirectionmethodofmultipliers[J].IEEETransactionsonEnergyConversion,2014,29(4):968-977.
[14] Baran M,Wu F F.Optimal sizing of capacitors placed onaradialdistributionsystem[J].IEEETransactionsonPower Delivery,1989,4(1):735-743.
[15] Dall’AneseE,DhopleSV,GiannakisGB.Optimaldispatchofphotovoltaicinvertersinresidentialdistribution systems[J].IEEE Transactions on SustainableEnergy,2014,5(2):487-497.
[16] Zheng Weiye,Wu Wenchuan,Zhang Boming,et al.Fullydistributedmulti-areaeconomicdispatchmethodforactivedistributionnetworks[J]. IETGeneration,Transmission&Distribution,2015,9(12):1341-1351.
[17] Boyd S,Parikh N,Chu E,et al.Distributed optimizationand statistical learning via the alternating direction methodofmultipliers[J].FoundationsandTrends?inMachineLearning,2011,3(1):1-122.
[18] Kraning M,Chu E,Lavaei J,et al.Dynamic networkenergymanagementviaproximalmessagepassing[J].Foundations and Trends in Optimization,2014,1(2):73-126.
[19]李佩杰,陆镛,白晓清,等.基于交替方向乘子法的动态经济调度分散式优化[J].中国电机工程学报,2015,35(10):2428-2435.Li Peijie,Lu Yong,Bai Xiaoqing,et al.Decentralizedoptimizationfordynamiceconomicdispatchbasedonalternating direction method of multipliers[J].Proceedingsof the CSEE,2015,35(10):2428-2435(in Chinese).
[20] BaranME, WuFF. Networkreconfigurationindistributionsystemsforlossreductionandloadbalancing[J].IEEETransactionsonPowerDelivery,1989,4(2):1401-1407.
[21] Zhang Dong,Fu Zhengcai,Zhang Liuchun.An improvedTSalgorithmforloss-minimumreconfigurationinlarge-scaledistributionsystems[J]. ElectricPowerSystems Research,2007,77(5-6):685-694.